{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#hide\n",
    "!pip install -Uqq fastbook\n",
    "import fastbook\n",
    "fastbook.setup_book()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fastbook import *"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "[appendix]\n",
    "[role=\"Jupyter notebook 101\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Appendix: Jupyter Notebook 101"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can read this tutorial in the book, but we strongly suggest reading it in a (yes, you guessed it) Jupyter Notebook. This way, you will be able to actually *try* the different commands we will introduce here. If you followed one of our tutorials in the previous section, you should have been left in the course folder. Just click on `nbs` then `dl1` and you should find the tutorial named `00_notebook_tutorial`. Click on it to open a new tab and you'll be ready to go.\n",
    "\n",
    "If you are on your personal machine, clone the course repository and navigate inside before following the same steps.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's build up from the basics: what is a Jupyter Notebook? Well, we wrote this book using Jupyter Notebooks. A notebook is a document made of cells. You can write in some of them (markdown cells) or you can perform calculations in Python (code cells) and run them like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1+1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cool, huh? This combination of prose and code makes Jupyter Notebook ideal for experimentation: we can see the rationale for each experiment, the code, and the results in one comprehensive document. \n",
    "\n",
    "Other renowned institutions in academia and industry use Jupyter Notebook, including Google, Microsoft, IBM, Bloomberg, Berkeley and NASA among others. Even Nobel-winning economists [use Jupyter Notebooks](https://paulromer.net/jupyter-mathematica-and-the-future-of-the-research-paper/)  for their experiments and some suggest that Jupyter Notebooks will be the [new format for research papers](https://www.theatlantic.com/science/archive/2018/04/the-scientific-paper-is-obsolete/556676/).\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Writing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A type of cell in which you can write text is called a _Markdown cell_. [_Markdown_](https://en.wikipedia.org/wiki/Markdown) is a very popular markup language. To specify that a cell is Markdown you need to click in the drop-down menu in the toolbar and select Markdown.\n",
    "\n",
    "Click on the the '+' button on the left and select Markdown from the toolbar. Now you can type your first Markdown cell. Write 'My first markdown cell' and press run.\n",
    "\n",
    "![add](images/chapter1_add.png)\n",
    "\n",
    "You should see something like this:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "My first markdown cell"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now try making your first _Code_ cell: follow the same steps as before but don't change the cell type (when you add a cell its default type is _Code_). Type something like 3/2. You should see '1.5' as output."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.5"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "3/2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Modes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you made a mistake in your *Markdown* cell and you have already run it, you will notice that you cannot edit it just by clicking on it. This is because you are in **Command Mode**. Jupyter Notebooks have two distinct modes:\n",
    "\n",
    "- Edit Mode:: Allows you to edit a cell's content.\n",
    "\n",
    "- Command Mode:: Allows you to edit the notebook as a whole and use keyboard shortcuts but not edit a cell's content. \n",
    "\n",
    "You can toggle between these two by either pressing <kbd>ESC</kbd> and <kbd>Enter</kbd> or clicking outside a cell or inside it (you need to double click if it's a Markdown cell). You can always tell which mode you're on: the current cell will have a green border in **Edit Mode** and a blue border in **Command Mode**. Try it!\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Other Important Considerations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Your notebook is autosaved every 120 seconds. If you want to manually save it you can just press the save button on the upper left corner or press <kbd>s</kbd> in **Command Mode**.\n",
    "\n",
    "![Save](images/chapter1_save.png)\n",
    "\n",
    "To know if your *kernel* (the Python engine executing your instructions behind the scenes) is computing or not, you can check the dot in your upper right corner. If the dot is full, it means that the kernel is working. If not, it is idle. You can place the mouse on it and the state of the kernel will be displayed.\n",
    "\n",
    "![Busy](images/chapter1_busy.png)\n",
    "\n",
    "There are a couple of shortcuts you must know about which we use **all** the time (always in **Command Mode**). These are:\n",
    "\n",
    " - Shift+Enter:: Run the code or markdown on a cell\n",
    " \n",
    " - Up Arrow+Down Arrow:: Toggle across cells\n",
    " \n",
    " - b:: Create new cell\n",
    " \n",
    " - 0+0:: Reset Kernel\n",
    "\n",
    "You can find more shortcuts by typing <kbd>h</kbd> (for help).\n",
    "\n",
    "You may need to use a terminal in a Jupyter Notebook environment (for example to git pull on a repository). That is very easy to do: just press 'New' in your Home directory and 'Terminal'. Don't know how to use the Terminal? We made a tutorial for that as well. You can find it [here](https://course.fast.ai/terminal_tutorial.html).\n",
    "\n",
    "![Terminal](images/chapter1_terminal.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That's it. This is all you need to know to use Jupyter Notebooks. That said, we have more tips and tricks below, so don't jump to the next section just yet.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Markdown Formatting\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Italics, Bold, Strikethrough, Inline, Blockquotes and Links"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The five most important concepts to format your code appropriately when using Markdown are:\n",
    "    \n",
    "- *Italics*:: Surround your text with \\_ or \\*.\n",
    "\n",
    "- **Bold**:: Surround your text with \\__ or \\**.\n",
    "\n",
    "- `inline`:: Surround your text with \\`.\n",
    "\n",
    "- blockquote:: Place \\> before your text.\n",
    "\n",
    "- [Links](http://course-v3.fast.ai/):: Surround the text you want to link with \\[\\] and place the link adjacent to the text, surrounded with ().\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Headings"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that including a hashtag before the text in a markdown cell makes the text a heading. The number of hashtags you include will determine the priority of the header (# is level one, ## is level two, ### is level three and #### is level four). We will add three new cells with the + button on the left to see how every level of heading looks.\n",
    "\n",
    "In the notebook, double click on some headings and find out what level they are!\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Lists"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are three types of lists in markdown.\n",
    "\n",
    "Ordered list:\n",
    "\n",
    "1. Step 1\n",
    "    2. Step 1B\n",
    "3. Step 3\n",
    "\n",
    "Unordered list\n",
    "\n",
    "* learning rate\n",
    "* cycle length\n",
    "* weight decay\n",
    "\n",
    "Task list\n",
    "\n",
    "- [x] Learn Jupyter Notebooks\n",
    "    - [x] Writing\n",
    "    - [x] Modes\n",
    "    - [x] Other Considerations\n",
    "- [ ] Change the world\n",
    "\n",
    "In the notebook, double click on them to see how they are built! \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Code Capabilities"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Code** cells are different than **Markdown** cells in that they have an output cell. This means that we can _keep_ the results of our code within the notebook and share them. Let's say we want to show a graph that explains the result of an experiment. We can just run the necessary cells and save the notebook. The output will be there when we open it again! Try it out by running the next four cells."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import necessary libraries\n",
    "from fastai.vision.all import * \n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from PIL import Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 2, 4, 8)"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = 1\n",
    "b = a + 1\n",
    "c = b + a + 1\n",
    "d = c + b + a + 1\n",
    "a, b, c ,d"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([a,b,c,d])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also print images while experimenting."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=197x250 at 0x7F3E279ABE50>"
      ]
     },
     "execution_count": null,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image.open(image_cat())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Running the App Locally"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You may be running Jupyter Notebook from an interactive coding environment like Gradient, Sagemaker or Salamander. You can also run a Jupyter Notebook server from your local computer. What's more, if you have installed Anaconda you don't even need to install Jupyter (if not, just `pip install jupyter`).\n",
    "\n",
    "You just need to run `jupyter notebook` in your terminal. Remember to run it from a folder that contains all the folders/files you will want to access. You will be able to open, view, and edit files located within the directory in which you run this command but not files in parent directories.\n",
    "\n",
    "If a browser tab does not open automatically once you run the command, you should CTRL+CLICK the link starting with 'http://localhost:' and this will open a new tab in your default browser.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Creating a Notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now that you have your own Jupyter Notebook server running, you will probably want to write your own notebook. Click on 'New' in the upper left corner and 'Python 3' in the drop-down list (we are going to use a [Python kernel](https://github.com/ipython/ipython) for all our experiments).\n",
    "\n",
    "![new_notebook](images/chapter1_new_notebook.png)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Shortcuts and Tricks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is a list of useful tricks when in a Jupyter Notebook. Make sure you learn them early and use them as often as you can!\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Command Mode Shortcuts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are a couple of useful keyboard shortcuts in `Command Mode` that you can leverage to make Jupyter Notebook faster to use. Remember that you can switch back and forth between `Command Mode` and `Edit Mode` with <kbd>Esc</kbd> and <kbd>Enter</kbd>.\n",
    "\n",
    "- m:: Convert cell to Markdown\n",
    "- y:: Convert cell to Code\n",
    "- d+d:: Delete cell\n",
    "- o:: Toggle between hide or show output\n",
    "- Shift+Arrow up/Arrow down:: Select multiple cells. Once you have selected them you can operate on them like a batch (run, copy, paste etc).\n",
    "- Shift+M:: Merge selected cells\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cell Tricks"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are also some tricks that you can code into a cell:\n",
    "\n",
    "- `?function-name`:: Shows the definition and docstring for that function\n",
    "- `??function-name`:: Shows the source code for that function\n",
    "- `doc(function-name)`:: Shows the definition, docstring **and links to the documentation** of the function\n",
    "(only works with fastai library imported)\n",
    "- Shift+Tab (press once):: See which parameters to pass to a function \n",
    "- Shift+Tab (press three times):: Get additional information on the method"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Line Magics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Line magics are functions that you can run on cells. They should be at the beginning of a line and take as an argument the rest of the line from where they are called. You call them by placing a '%' sign before the command. The most useful ones are:\n",
    "\n",
    "- `%matplotlib inline`:: Ensures that all matplotlib plots will be plotted in the output cell within the notebook and will be kept in the notebook when saved.\n",
    "\n",
    "This command is always called together at the beginning of every notebook of the fast.ai course.\n",
    "\n",
    "``` python\n",
    "%matplotlib inline\n",
    "```\n",
    "\n",
    "- `%timeit`:: Runs a line ten thousand times and displays the average time it took to run."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "56.1 µs ± 592 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit [i+1 for i in range(1000)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`%debug`: Inspects a function which is showing an error using the [Python debugger](https://docs.python.org/3/library/pdb.html). If you type this in a cell just after an error, you will be directed to a console where you can inspect the values of all the variables.\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
